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the department not be able to fill its positions. Positions listed below may or may not be available, depending on need. For more information about this position, contact ridgs@umn.edu This Position is covered by
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efforts to contribute to safer marine operations, we actively explore possibilities to utilize both numerical and machine learning methods to enhance the accuracy and resolution of metocean forecasts. About
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reducing waiting lists. This will be achieved through the following objectives: Acquire data and expert-based evidence and optimise data augmentation to ensure optimal hospital patient pathways through pre
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: The main place of work will be at our campus in Halden, but some presence at our campus in Fredrikstad may be expected. Project description Project title: My AI Co-worker: Exploring AI for Computer Supported
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need expert knowledge in bioinformatic data analysis. Strong expertise in multi-omics data analysis (using R and Python) and a deep understanding of machine-learning models are must-criteria
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background in CMOS/VLSI design, computer architectures (preferred RISC-V architecture), and deep learning principles. Experience with industry-standard EDA tools such as Cadence suite: Genus, Virtuoso, Spectre
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, statistical analysis, and machine learning techniques to predict market behavior and generate alphas Execution. Create strategies to execute on modelling ideas under simulated competition Evaluation. Backtest
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theory, statistical analysis, and machine learning techniques to predict market behavior and generate alphas Execution. Create strategies to execute on modelling ideas under simulated competition
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, execution efficiency, and live trading performance. What you can expect Modelling. Apply probability theory, statistical analysis, and machine learning techniques to analyze and interpret market behavior
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the controlled flow at tunable temperature and photopolymerization of the precursor. The practical work will be complemented by fluid mechanics computer simulations, including solutions employing machine learning